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A Multistage Deep Belief Networks Application on Arrhythmia Classification
2016
International Journal of Intelligent Systems and Applications in Engineering
An electrocardiogram (ECG) is a biomedical signal type that determines the normality and abnormality of heart beats using the electrical activity of the heart and has a great importance for cardiac disorders. The computer-aided analysis of biomedical signals has become a fabulous utilization method over the last years. This study introduces a multistage deep learning classification model for automatic arrhythmia classification. The proposed model includes a multi-stage classification system
doi:10.18201/ijisae.2016specialissue-146978
fatcat:sofr5ae3ivbuvicqcy73w5lshy